Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only provide generic hints (readOnlyHint=false, openWorldHint=true, idempotentHint=false). The description shoulders the burden and does so well: it discloses that the tool sends a message to a human, replies typically within one business day, transmits only the requester's name/email/organization/use case, and nothing else from the conversation. This is exactly the behavioral context an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each with a distinct job: purpose plus latency, when to use, and privacy/consent condition. No repetition or filler, and the most important facts are front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and openWorldHint=true, the description covers purpose, usage conditions, data transmitted, expected latency, and authorization. It does not name sibling tools explicitly in the usage guidance, and it does not describe the response format, but for a human-action tool this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds some value by enumerating which fields are transmitted and reassuring that no other conversation data is sent, but it does not meaningfully enrich the meaning of individual parameters like model or country beyond what the schema already says.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Submit') and resource ('a purchase or quote inquiry for a robot model to the BotInfo team'), and immediately clarifies the result is a human-prepared quote. It clearly distinguishes itself from siblings like get_buy_route and lookup_robot by focusing on quote requests rather than routing or lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use conditions: models with no live purchase route, destinations routed checkouts cannot fulfil, and volume/education/research/enterprise purchases. It also gives a firm exclusion: call it only when the requester has asked for a quote and has provided their own contact details.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.